In vivo growth of 60 non-screening detected lung cancers: a computed tomography study

Discussion

To our knowledge, this is the first study to evaluate in vivo growth of lung cancer in humans originating from a non-screening, daily routine-care setting. Our results from a substantially large cohort of lung cancers provide an experimental basis for the theoretically assumed exponential growth pattern.

Due to the fact that sequential CT imaging of untreated malignancies is rarely possible in humans, data on growth of human lung cancer are extremely limited in literature. The trend of more frequent CT imaging, improved CT technique and advanced software tools enabled us to study the growth behaviour of 60 histologically proven non-screen-detected malignancies. Since current management guidelines for the follow-up of incidentally and screen-detected nodules assume exponential growth to differentiate malignancies from benign lesions [7, 8], the validity of the growth behaviour model has become very important. Deviation of actual growth from the theoretical model may lead to under- or overtreatment of nodules.

Only two prior studies specifically analysed growth patterns of human lung cancers, both using lung cancer screening CT data [5, 6]. Lindell et al. [5] reported a variety of growth curves in 18 medium-sized lung cancers (median 10.3 mm), both solid and subsolid lesions. In their study one observer manually measured lesions diameter using callipers on fairly thick slices. Lesion volume was calculated assuming a perfect spherical lesion shape. Ultimately, plotted growth curves with at least four time points over a follow-up interval of at median 2.9 years were assessed visually. The authors concluded that in their cohort lung cancers were not limited to exponential growth and warned for misinterpretation using exponential-based equations [5]. In contrast, Heuvelmans et al. [6] assessed growth patterns more meticulously in 47 small solid screen-detected lung cancers with a median baseline volume of 100 mm³. They assessed growth curves with at least three time points over a median follow-up interval of a 2.1 years, using semi-automated nodule volumetry and quantitative analysis. They concluded that small- to intermediate-sized lung malignancies can generally be described by an exponential function [6]. Additionally, a small study by Quint et al. [11] assessed doubling times of various lung lesions, including 13 primary lung cancers. They showed that growth curves were visually fairly consistent with exponential increase; however, no further statistical analysis was performed. Differences in study populations with respect to number and type of nodules, as well as differences in growth measurement methods, are likely to have contributed to the opposing conclusions of the available studies [12].

In our study we used semi-automated volumetry instead of either manual measurements or visual growth curve assessment to analyse lung cancer growth over time, and included a fairly large number of 60 lung cancers. We included both solid and subsolid lesions, originating from a heterogeneous routine-care clinical population. Although data on risk factors and smoking history were unavailable in our study, our study population is essentially different from a homogeneous lung cancer screening population because it is not highly selected on age and smoking history. Additionally, all had a clinical indication for chest imaging, and prior malignancies were not excluded as they were in previous screening studies.

We confirmed statistically that growth in lung cancers was exponential in both solid and subsolid lesions, although on a per lesion base some deviation from the predicted exponential volume increase was seen. The magnitude of deviations showed a median close to zero (i.e. 2%, IQR −11–18%), which falls inside the range of 25% volume change that has been posed as a threshold for significant volume change [8, 10]. Variations in individual lung cancers will at least partly be due to technical differences between scans and some measurement errors, the latter being larger in smaller lesions and shorter follow-up [8, 10, 13]. Nevertheless, real deviations from the exponential growth may exist in some cases. However, these individual outliers were not sufficient to reject the conclusion that an exponential function best describes in vivo lung cancer growth in humans. Therefore, current clinical decision tools are correct in their assumption of exponential growth.

In addition to confirming the exponential nature of lung cancer growth in our dataset, we found that subsolid lesions are generally larger than solid ones at baseline, but show significantly slower progression over time. This is in line with previous literature that reported the generally smaller growth rate of subsolid lesions. As a consequence, management guidelines recommend larger intervals and a longer follow-up time for subsolid than for solid nodules [7, 8]. Although different in terms of baseline size and growth rate, both solid and subsolid nodules showed an exponential growth pattern. According to our results, baseline volume is not related to speed of growth over time, indicating that smaller lung lesions do not necessarily grow more slowly. Knowledge of individual growth behaviour may be used to further personalise follow-up intervals, which might vary for lesions within the same nodule type subgroup. This strategy is currently not effected in the guidelines, as intervals recommended are similar for all nodules within a certain subgroup. Future studies are needed to evaluate whether it is feasible, safe and cost effective to base follow-up strategy on individual growth behaviour instead of baseline volume only. However, it has to be noted that a total of three or more scans are needed to determine exponential behaviour. Therefore, it is most likely best applied in subsolid lesions that are often subject to long-term follow-up and in which overdiagnosis lingers [14], but it might also be applicable for a selected subgroup of slow-growing solid lesions.

The inherent and major limitation of our study is the possible selection bias towards smaller and more slowly growing lesions. Exponential growth pattern analysis requires at least three imaging time points, which automatically eliminates the fast-growing nodules and larger lesions that are more likely to be referred for immediate (therapeutic) actions without further follow-up. Growth rate differences between the included cancers with three or more imaging time points and lung cancers only imaged twice did not reach significance. Nevertheless, the possibility remains that some larger fast-growing lung cancers do not grow exponentially. Additionally, selection bias may have played a role in the difference we observed in baseline volume between solid and subsolid lesions. When smaller subsolid nodules have not progressed enough to warrant intervention/definitive diagnosis, they are not included. In addition, smaller subsolid nodules may be ignored and are more difficult to detect due to their morphology, which may be another reason they are not included in our study.

A second limitation is the retrospective nature of our study, which is less optimal due to the fact that the data are more heterogeneous. However, we believe a prospective design is ethically unacceptable in humans. Nevertheless, with this retrospective study design we were able to confirm the theory of the exponential growth model and echo the most recent data obtained in lung cancer screening setting.

In conclusion, we present the first study outside the lung cancer screening setting evaluating in vivo growth behaviour of solid and subsolid lung cancers in humans. We show that primary lung cancer growth conforms to an exponential model in both subsolid and solid lesions. This provides the first experimental basis in routine-care setting for the assumption made in VDT analysis. Therefore, current nodule management guidelines are correct in their assumption, and reasonable to use in the follow-up of lung nodules in routine care.